Since AlexNet [1]} won the 2012 ImageNet competition, Convolutional Neural Networks (ConvNets) have been increasingly used as the de facto standard for image segmentation tasks. Although higher accuracy is critical for autonomous driving applications, we have already hit the hardware memory limit for the image segmentation tasks using ConvNets. Thus further accuracy gains will require better efficiency.
